Article type
Abstract
Background: In September 2016 Cochrane received a grant from the Bill and Melinda Gates Foundation to accelerate our development of a 'next generation evidence system' in the areas of maternal and child health in support of the Gates Foundation’s ‘Healthy Birth Growth and Development Knowledge Integration' (HBGDki) initiative. The main aim was to use technology, domain experts, and the Crowd to create processes and tools to better curate evidence to improve discoverability.
Objectives: This presentation will give an update on the development and outcomes of this 6-month project, including key deliverables, metrics, and integration with Cochrane internal systems, as well as partners in the HBGDki community. We will introduce the key components of this work: the Cochrane Linked Data infrastructure, machine-learning evidence pipeline system, and the Cochrane Crowd component, and how they work together with domain experts, information specialists and a team of annotators and ontology developers to deliver a next-generation paradigm for evidence curation.
Methods: We will describe the technical development, ontology development, and engagement activities. Descriptions of the various tools, processes, and data structures used will be provided as well as any preliminary validation that was done on performance. Issues encountered and methods used to overcome them will be discussed and explored.
Results: A summary of the key outcomes and measures of success for the project, including next steps for this work across the wider Cochrane community and dataset will be discussed as well as the implications for future development of Cochrane systems and processes.
Conclusions: Cochrane successfully completed a 6-month project with the Bill and Melinda Gates Foundation and key partners to accelerate the delivery of a next-generation evidence system for curation of maternal and child-health evidence. Lessons learned and next steps to inform future development within Cochrane and also potential future projects with Gates and partners will be discussed.
Objectives: This presentation will give an update on the development and outcomes of this 6-month project, including key deliverables, metrics, and integration with Cochrane internal systems, as well as partners in the HBGDki community. We will introduce the key components of this work: the Cochrane Linked Data infrastructure, machine-learning evidence pipeline system, and the Cochrane Crowd component, and how they work together with domain experts, information specialists and a team of annotators and ontology developers to deliver a next-generation paradigm for evidence curation.
Methods: We will describe the technical development, ontology development, and engagement activities. Descriptions of the various tools, processes, and data structures used will be provided as well as any preliminary validation that was done on performance. Issues encountered and methods used to overcome them will be discussed and explored.
Results: A summary of the key outcomes and measures of success for the project, including next steps for this work across the wider Cochrane community and dataset will be discussed as well as the implications for future development of Cochrane systems and processes.
Conclusions: Cochrane successfully completed a 6-month project with the Bill and Melinda Gates Foundation and key partners to accelerate the delivery of a next-generation evidence system for curation of maternal and child-health evidence. Lessons learned and next steps to inform future development within Cochrane and also potential future projects with Gates and partners will be discussed.